This paper describes interaction potentials by universal function
approximators in the form of deep neural networks. In this form, Social Forces are
derived from gradients of the neural network using automatic differentiation
with efficient BackProp [1]}. The same automatic
differentiation implementation is used to compute the gradients of these
potentials.
